2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)最新文献_第4页

Dynamic, self-organized clusters as a means to supply and demand matching in large-scale energy systems 动态、自组织集群作为大规模能源系统供需匹配的手段

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000154

Selma Čaušević, M. Warnier, F. Brazier

引用次数: 12

Empirical analysis of collaborative filtering-based recommenders in temporally evolving systems 时间演化系统中基于协同过滤的推荐的实证分析

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000127

Xiaoyu Shi, Xin Luo, Mingsheng Shang, Xin-Yi Cai

{"title":"Empirical analysis of collaborative filtering-based recommenders in temporally evolving systems","authors":"Xiaoyu Shi, Xin Luo, Mingsheng Shang, Xin-Yi Cai","doi":"10.1109/ICNSC.2017.8000127","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000127","url":null,"abstract":"Recommender systems benefit people's daily lives at every moment. While considerable attentions have been drawn by performance in one-step recommendation and static user-item network, recommenders' performance on temporally evolving networks remains unclear. To address this issue, this paper firstly adopts a bipartite network to describe the online commercial system. We then propose a network evolution method to simulate the mutual feedback between recommender system and its users' decisions in the evolving network with time. To investigate the long-term performance of three state-of-the-art CF-based recommenders, i.e., the user-based collaborative filtering (UCF), item-based collaborative filtering (ICF) and latent factor-based model (LFM), this online network is evolving with time driven by each tested recommender. Besides using root mean squared error (RMSE) to evaluate prediction accuracy of recommender, we also calculate the intra-similarity and popularity to study the performance of recommendation, as well as Gini coefficient to evaluate the health of online network. Experiments on two real datasets, we find that during the temporal evolving process LFM's accuracy loss is less than that of UCF and ICF, besides LFM enjoys a high accuracy in one-step recommendation. Moreover, although LFM proves to be highly accurate and stable during the temporal evolving network, ICF shows a better performance than LFM in terms of recommendation diversity, and it simultaneously benefits the health of online system. Hence, these results provide insights for the design of a next generation of recommender systems, which would tradeoffs between short- and long-term performances.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"212 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114166418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Link available time prediction based GPSR for vehicular ad hoc networks 基于GPSR的车辆自组织网络链路可用时间预测

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000107

Haojun Yang, Ming Yu, Xuming Zeng

引用次数: 18

Multi-dimension and multi-granularity segmentation of remote sensing image based on improved Otsu algorithm 基于改进Otsu算法的遥感图像多维多粒度分割

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000172

Dongmei Huang, Jingqi Sun, Shuang Liu, Shoujue Xu, Suling Liang, Cong Li, Zhenhua Wang

{"title":"Multi-dimension and multi-granularity segmentation of remote sensing image based on improved Otsu algorithm","authors":"Dongmei Huang, Jingqi Sun, Shuang Liu, Shoujue Xu, Suling Liang, Cong Li, Zhenhua Wang","doi":"10.1109/ICNSC.2017.8000172","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000172","url":null,"abstract":"An increasing number of unknown islands, an important resource for human development, is identified based on segmentation of remote sensing image. Different from traditional digital image, remote sensing image has significant characteristics, such as multi-band, multi-source, and multi-granularity. Thus, the segmentation theory based on traditional digital image is not suitable for remote sensing image. Here, the segmentation algorithm (Otsu), which is a common method for traditional digital image, was improved in two aspects: (1) Based on PCA and band fusion, the Otsu algorithm with one-dimensional image was extended to multi-dimensional ones; (2) By optimizing the threshold value, the Otsu algorithm for single feature extraction was extended to multi-granularity extraction. Taking the island segmentation from remote sensing image as an example, the improved Otsu algorithm was compared with the traditional Otsu: 1) Through using PCA algorithm, multi-band remote sensing image was reduced to effective 3–4 new bands; 2) Through different threshold settings, the objects in the remote sensing image are divided into different classes; 3) The improved Otsu algorithm reduces the computational complexity, taking the threshold value of 2 as an example, the time efficiency is improved by 42.15%.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127020735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Petri net based software testing scheduling and selecting 基于Petri网的软件测试调度与选择

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000086

Senke Ding, Peifu Xu, Weimin Wu, Yi Yang, Zichao Xing, Feihua Lu, Cheng Li

引用次数: 0

PalmNET: An open-source wireless sensor network for oil palm plantations PalmNET:用于油棕种植园的开源无线传感器网络

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000190

M. Culman, J. Portocarrero, C. Guerrero, C. Bayona, J. L. Torres, C. Farias

引用次数: 9

Adaptive neuro-fuzzy predictive control for design of adaptive cruise control system 基于自适应神经模糊预测控制的自适应巡航控制系统设计

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000187

Yu‐Chen Lin, H. Nguyen, Cheng-Hsien Wang

{"title":"Adaptive neuro-fuzzy predictive control for design of adaptive cruise control system","authors":"Yu‐Chen Lin, H. Nguyen, Cheng-Hsien Wang","doi":"10.1109/ICNSC.2017.8000187","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000187","url":null,"abstract":"Proliferation of the number of vehicles is one of the main causes of traffic congestion, accidents, energy waste and environmental pollution. Recently, several intelligent applications are equipped in modern vehicles such as advanced driver assistance systems (ADAS), especially an adaptive cruise control (ACC) system which was successfully implemented on some luxury cars and still remains to be an interesting topic of research. An adaptive neuro-fuzzy predictive control (ANFPC) is proposed in designing of ACC system in this paper. By controlling the ACC vehicle through the throttle force or brakes, the ACC vehicle follows its predecessor and maintains the safe distance with the minimized tracking error. In the ANFPC scheme, a Takagi-Sugeno (T-S) fuzzy model is utilized to approximate the preceding vehicle model and then the predicted state sequence of the preceding vehicle is obtained. More importantly, the predictive control law is derived by a fuzzy neural networks (FNNs) approach. Simulation results demonstrate that the proposed ANFPC can achieve better performance than other methods in terms of safety, comfort and fuel consumption, simultaneously.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"22 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132845978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

An unsupervised approach in learning load patterns for non-intrusive load monitoring 非侵入式负载监测中学习负载模式的无监督方法

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000164

Saman Mostafavi, R. Cox

引用次数: 6

A modelling & simulation based engineering approach for socio-cyber-physical systems 基于建模和仿真的社会-网络-物理系统工程方法

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000176

Thuy Nguyen

{"title":"A modelling & simulation based engineering approach for socio-cyber-physical systems","authors":"Thuy Nguyen","doi":"10.1109/ICNSC.2017.8000176","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000176","url":null,"abstract":"Today, most large and complex systems such as aircrafts or power grids integrate physical and human aspects with computing and networking, and therefore constitute so-called socio-cyber-physical systems (SCPS). Their engineering, from prospective and conceptual studies (to determine the scope of the system) through design and construction to operation, maintenance and upgrades, necessitates the cooperation and coordination of many teams representing different disciplines and viewpoints. In addition, such systems are subject to many constraints such as tight budget and schedule; high dependability, safety and security; need to innovate; long lifetime; changing and uncertain environments. This paper presents a modelling and simulation (M&S) based engineering approach that can address the challenges of large and complex SCPS, and more generally, of systems of SCPS (SoS). Contrary to “classical” M&S approaches relying on deterministic behavioural models that can be developed only in the final stages of the design process, the proposed approach relies on constraints models that specify envelopes of required or assumed behaviours, and that can be applied at any phase of the system lifecycle. Also, in order to manage complexity and the variety of viewpoints, the approach supports models composition, whereby models from different teams or at different phases of the process can be aggregated (top-down or bottom-up) and verified for consistency.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133492667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Load balancing for minimizing the average response time of get operations in distributed key-value stores 用于最小化分布式键值存储中get操作的平均响应时间的负载平衡

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000102

Antonios Makris, K. Tserpes, D. Anagnostopoulos, J. Altmann

引用次数: 10